CN116773686A - Method and system for measuring content of ketone compounds in swertia davidiana - Google Patents
Method and system for measuring content of ketone compounds in swertia davidiana Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 85
- -1 ketone compounds Chemical class 0.000 title claims abstract description 75
- 241001530209 Swertia Species 0.000 title claims abstract description 41
- 241000974657 Swertia pseudochinensis Species 0.000 claims abstract description 37
- 238000005259 measurement Methods 0.000 claims abstract description 26
- 150000002576 ketones Chemical class 0.000 claims abstract description 15
- 238000004128 high performance liquid chromatography Methods 0.000 claims abstract description 11
- 238000007781 pre-processing Methods 0.000 claims abstract description 10
- 230000003595 spectral effect Effects 0.000 claims abstract description 6
- AEDDIBAIWPIIBD-ZJKJAXBQSA-N mangiferin Chemical compound O[C@@H]1[C@@H](O)[C@H](O)[C@@H](CO)O[C@H]1C1=C(O)C=C(OC=2C(=CC(O)=C(O)C=2)C2=O)C2=C1O AEDDIBAIWPIIBD-ZJKJAXBQSA-N 0.000 claims description 38
- 238000000605 extraction Methods 0.000 claims description 34
- YWQSXCGKJDUYTL-UHFFFAOYSA-N Mangiferin Natural products CC(CCC=C(C)C)C1CC(C)C2C3CCC4C(C)(C)CCCC45CC35CCC12C YWQSXCGKJDUYTL-UHFFFAOYSA-N 0.000 claims description 19
- 150000001875 compounds Chemical class 0.000 claims description 19
- 229940043357 mangiferin Drugs 0.000 claims description 19
- 238000002329 infrared spectrum Methods 0.000 claims description 18
- 239000000284 extract Substances 0.000 claims description 16
- HEYZWPRKKUGDCR-QBXMEVCASA-N Swertiamarin Chemical compound O[C@@H]1[C@@H](O)[C@H](O)[C@@H](CO)O[C@H]1O[C@H]1[C@H](C=C)[C@]2(O)CCOC(=O)C2=CO1 HEYZWPRKKUGDCR-QBXMEVCASA-N 0.000 claims description 11
- HEYZWPRKKUGDCR-WRMJXEAJSA-N Swertiamarin Natural products O([C@H]1[C@H](O)[C@@H](O)[C@H](O)[C@@H](CO)O1)[C@H]1[C@@H](C=C)[C@@]2(O)C(C(=O)OCC2)=CO1 HEYZWPRKKUGDCR-WRMJXEAJSA-N 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 11
- 239000007788 liquid Substances 0.000 claims description 10
- 239000000843 powder Substances 0.000 claims description 9
- 238000012795 verification Methods 0.000 claims description 9
- 238000012937 correction Methods 0.000 claims description 7
- 238000005457 optimization Methods 0.000 claims description 6
- 238000004587 chromatography analysis Methods 0.000 claims description 5
- 238000002474 experimental method Methods 0.000 claims description 4
- DUAGQYUORDTXOR-GPQRQXLASA-N Gentiopicrin Chemical compound O[C@@H]1[C@@H](O)[C@H](O)[C@@H](CO)O[C@H]1O[C@H]1[C@H](C=C)C2=CCOC(=O)C2=CO1 DUAGQYUORDTXOR-GPQRQXLASA-N 0.000 claims description 3
- DUAGQYUORDTXOR-WULZUDSJSA-N Gentiopicrin Natural products O([C@H]1[C@H](O)[C@@H](O)[C@H](O)[C@@H](CO)O1)[C@H]1[C@@H](C=C)C=2C(C(=O)OCC=2)=CO1 DUAGQYUORDTXOR-WULZUDSJSA-N 0.000 claims description 3
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- 238000012628 principal component regression Methods 0.000 claims description 3
- 241000759904 Davidia Species 0.000 claims 1
- 239000000126 substance Substances 0.000 abstract description 5
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- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 18
- 230000000694 effects Effects 0.000 description 11
- OZWDYLLMBFLSNH-UHFFFAOYSA-N Swertisin Natural products COc1cc2OC(=CC(=O)c2c(O)c1OC3OC(CO)C(O)C(O)C3O)c4cccc(O)c4 OZWDYLLMBFLSNH-UHFFFAOYSA-N 0.000 description 9
- 238000010521 absorption reaction Methods 0.000 description 9
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- ABRULANJVVJLFI-DGHBBABESA-N swertisin Chemical compound COC1=CC=2OC(C=3C=CC(O)=CC=3)=CC(=O)C=2C(O)=C1[C@@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O ABRULANJVVJLFI-DGHBBABESA-N 0.000 description 9
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- BDAGIHXWWSANSR-UHFFFAOYSA-N methanoic acid Natural products OC=O BDAGIHXWWSANSR-UHFFFAOYSA-N 0.000 description 2
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- OSWFIVFLDKOXQC-UHFFFAOYSA-N 4-(3-methoxyphenyl)aniline Chemical compound COC1=CC=CC(C=2C=CC(N)=CC=2)=C1 OSWFIVFLDKOXQC-UHFFFAOYSA-N 0.000 description 1
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
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Abstract
The invention discloses a swertia pseudochinensisThe method and system for measuring the content of the ketone compounds comprise the following steps: collecting swertia pseudochinensis at different months as a sample; determination of the sample using high performance liquid chromatographyThe ketone components are differentKetone compoundsContent measurement results of the substance; respectively collecting infrared spectrograms of samples of each month, and comparing infrared spectrogram characteristics of samples of different months; combining infrared spectral features to create differencesA quantitative model of a ketone compound, which is optimized by using different modeling methods and/or spectrogram preprocessing methods; using multiple indexes to evaluate the quantitative model and combining the quantitative model with the content measurement result to obtain different valuesAn optimal quantitative model of the ketone compound; determination of the differences in the swertia pseudochinensis using an optimal quantitative modelThe content of ketone compounds. The invention can rapidly and correctly measure the swertia pseudochinensisThe content of the ketone compounds provides a basis for the rapid quality identification of the swertia pseudochinensis.
Description
Technical Field
The invention relates to the technical field of compound content measurement, in particular to a method for measuring the content of a compound in swertiaMethod and system for measuring the content of ketone compounds.
Background
The swertia mussel is a plant of swertia genus of Gentianaceae family, and is a representative Tibetan medicine material, called "Tibetan medicineAnd (5) ageing. Swertia davidiana is grown in Qinghai, tibet, sichuan and Yunnan, and has an altitude of 1900-3800m.The ketone, also called benzochromone, is yellow or colorless and is a class of aromatic hydrocarbons with tricyclo (C 6 -C 3 -C 6 ) The natural product of the structure has higher occupation ratio in the swertia, and is separated and identified from the swertia at present>The number of ketone compounds is50 or more, and +.>The ketone compounds have antidepressant, antitumor, diabetes treating, vasodilating, and blood pressure lowering effects, because of +.>The ketone has important medicinal value and is very critical to the content measurement of the ketone in the swertia davidiana.
The quality detection of the traditional Chinese medicinal materials is commonly used as high performance liquid chromatography, ultraviolet spectrophotometry, UPLC (ultra-violet chromatography) method and the like, the methods need to separate the mixture first and then analyze the pure components or ingredients, so that the time and the labor are wasted, the most original information of the sample cannot be ensured, and the interaction and the integral relation of the chemical components of the medicinal materials cannot be reflected. Therefore, a more convenient, rapid and accurate method for analyzing and identifying the quality of medicinal materials is needed.
Disclosure of Invention
The invention aims to overcome the defects of the prior swertia pseudochinensisThe problem of the ketone compound determination technology is that a kind of +.f in swertia pseudolariciresifolia is provided>Method and system for measuring the content of ketone compounds.
The aim of the invention is realized by the following technical scheme:
in a first aspect, there is provided a method of producing a swertia pseudochinensisA method for determining the content of a ketone compound, the method comprising:
collecting swertia pseudochinensis at different months as a sample;
determination of the sample using high performance liquid chromatographyThe ketone component is extracted by ultrasonic method to obtain different +.>The content measurement result of the ketone compounds;
respectively collecting infrared spectrograms of samples of each month, and comparing infrared spectrogram characteristics of samples of different months;
establishing differences in combination with the infrared spectral featuresA quantitative model of a ketone compound, wherein the quantitative model is optimized using different modeling methods and/or spectrogram preprocessing methods;
using multiple indexes to evaluate the quantitative model and combining the content measurement results to verify the quantitative model to obtain different indexesAn optimal quantitative model of the ketone compound;
determining the difference in said swertia pseudochinensis using said optimal quantitative modelThe content of ketone compounds.
As a preferred option, a swertia pseudochinensisThe method for measuring the content of the ketone compounds collects the swertia pseudochinensis at different monthsDental dish as a sample, comprising:
and respectively collecting swertia pseudochinensis of 6-9 months, wherein 20 samples are collected each month.
As a preferred option, a swertia pseudochinensisMethod for determining the content of ketones, said different +.>The ketone compounds include mangiferin, swertiamarin and gentiopicrin.
As a preferred option, a swertia pseudochinensisThe content determination method of ketone compounds, the ultrasonic method optimizes component extraction, comprises the following steps:
optimizing extraction time, feed-liquid ratio, extraction concentration, extraction temperature and extraction power, designing an orthogonal experiment, and optimizing the most suitable extraction conditions through extremely poor analysis, variance analysis and comparison of a theoretical optimal combination and an actual optimal combination.
As a preferred option, a swertia pseudochinensisThe method for measuring the content of the ketone compounds comprises the steps of respectively collecting infrared spectrograms of samples of each month, wherein the infrared spectrograms comprise the following steps:
infrared spectra NIR were collected as powder samples and sample extracts, respectively.
As a preferred option, a swertia pseudochinensisMethod for determining the content of ketone compounds, said method combining said infrared spectral features to create different +.>A quantitative model for ketone compounds, comprising:
according to different situationsThe ketone compounds select different modeling wave bands.
As a preferred option, a swertia pseudochinensisThe modeling method comprises partial least square and principal component regression.
As a preferred option, a swertia pseudochinensisThe spectrogram preprocessing method comprises multi-element scattering correction, variable standardization, first derivative, second derivative and SG convolution smoothing.
As a preferred option, a swertia pseudochinensisThe indexes comprise modeling set correlation coefficient, verification set correlation coefficient, correction error root mean square, prediction error root mean square and residual error prediction deviation.
In a second aspect, a method of producing a swertia pseudochinensis is providedA system for determining the content of a ketone compound, the system comprising:
the sample collection unit is used for collecting swertia pseudochinensis at different months as a sample;
a chromatography content determination module for determining the sample using high performance liquid chromatographyThe ketone component is extracted by ultrasonic method to obtain different +.>The content measurement result of the ketone compounds;
the infrared spectrum acquisition module is used for respectively acquiring infrared spectrograms of samples of each month and comparing infrared spectrum characteristics of samples of different months;
the quantitative model building module is used for combining the infrared spectrum characteristics to build different types of imagesA quantitative model of a ketone compound, wherein the quantitative model is optimized using different modeling methods and/or spectrogram preprocessing methods;
the quantitative model optimization module is used for evaluating the quantitative model by using various indexes and verifying the quantitative model by combining the content measurement results to obtain different indexesAn optimal quantitative model of the ketone compound;
the content measurement module is used for measuring different swertia pseudochinensis in the optimal quantitative modelThe content of ketone compounds.
It should be further noted that the technical features corresponding to the above options may be combined with each other or replaced to form a new technical scheme without collision.
Compared with the prior art, the invention has the beneficial effects that:
(1) The invention combines the infrared spectrum characteristics to build differentQuantitative models of ketone compounds are optimized under different modeling methods, different spectrogram preprocessing methods and multiple index evaluation to obtain different +.>Optimal quantitative model of ketone compound can realize the aim of different +.>The rapid and accurate detection of ketone compounds provides for rapid quality identification of swertia pseudochinensisFor the basis. The measurement operation does not need expert knowledge, and the required time is greatly shortened compared with the traditional measurement method.
(2) In one example, the swertia pseudochinensis Franch of different months is taken as a sample for analysis, so that the biomass change condition of the swertia pseudochinensis Franch of different growth periods can be measured, and guidance is provided for cultivation of the swertia pseudochinensis Franch.
Drawings
FIG. 1 shows a method of producing a swertia pseudochinensisA flow chart of a method for measuring the content of ketone compounds;
FIG. 2 shows the biomass change of swertia pseudochinensis in different growth periods according to the embodiment of the invention;
FIG. 3 is a chromatographic separation of a standard according to an embodiment of the invention;
fig. 4 is a NIR spectrum of a crude drug and its extract according to an embodiment of the present invention;
FIG. 5 is a near infrared spectrum analysis showing an embodiment of the present invention;
FIG. 6 shows NIR, D1, D2 spectra and 3 species of the present inventionCorrelation of ketone compound models;
FIG. 7 shows the linear relationship between the predicted and measured values of three compound models according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully understood from the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
In an exemplary embodiment, a method of producing a swertia pseudochinensis is providedA method for determining the content of ketone compounds, referring to fig. 1, the method comprises:
collecting swertia pseudochinensis at different months as a sample;
determination of the sample using high performance liquid chromatographyThe ketone component is extracted by ultrasonic method to obtain different +.>The content measurement result of the ketone compounds;
respectively collecting infrared spectrograms of samples of each month, and comparing infrared spectrogram characteristics of samples of different months;
establishing differences in combination with the infrared spectral featuresA quantitative model of a ketone compound, wherein the quantitative model is optimized using different modeling methods and/or spectrogram preprocessing methods;
using multiple indexes to evaluate the quantitative model and combining the content measurement results to verify the quantitative model to obtain different indexesAn optimal quantitative model of the ketone compound;
determining the difference in said swertia pseudochinensis using said optimal quantitative modelThe content of ketone compounds.
The invention combines the infrared spectrum characteristics to build differentQuantitative model of ketone compound, and different modeling methods and different spectrogram pretreatment methodsOptimizing under multiple index evaluation to obtain different +.>Optimal quantitative model of ketone compound can realize the aim of different +.>The rapid and accurate detection of the ketone compounds provides basis for rapid quality identification of swertia pseudochinensis
Specifically, the swertia davidi used is two years old, and in one example, the collecting swertia davidi of different months as a sample includes:
and respectively collecting swertia pseudochinensis in the growth period of 6-9 months, wherein 20 samples are collected each month. Cleaning, air drying, pulverizing, and drying in a dryer.
Determination of the sample using high performance liquid chromatographyThe instruments and reagents previously prepared for the ketone component include: agilent 1260 high performance liquid chromatograph (Agilent, usa), nicolette iS50 fourier transform infrared spectrometer (zemoeid, usa), electronic balance (mertrer), reflux tube, absolute ethanol (AR), and methanol (chromatophore, merck).
For the samples obtained during each growth period, the growth and development characteristics thereof were measured, the leaf number, plant height, fresh weight, dry weight thereof were recorded, and the dry rate was calculated. Dry rate = dry weight (g)/wet weight (g) 100%. Specifically, the biomass change conditions of the swertia davidiana in different growth periods are shown in a figure 2, wherein a represents plant height, b represents leaf number, c represents fresh weight, d represents dry weight, e represents drying rate, and plant height is gradually increased in a period of 6-8 months until 9 months reach stability. The leaf number is in a growing trend in the research range, the increase of 9 months is large, and the plant biomass is in an increasing trend. The drying rate of swertia davidiana is also in an upward trend, which shows that the moisture in the plant body gradually decreases along with the growth of the plant.
Further, the chromatographic conditions are: ZORBAX SB-C18 column (4.6X 150mm,5um,Agilent Technologies, USA), sample size: 10 μl, flow rate: 1.0mL/min, column temperature: detection wavelength 254nm at 35 ℃, mobile phase: a-water (0.1% formic acid), B-100% methanol. Elution gradients are shown in table 1:
gradient elution procedure for Compounds of Table 1
In one example, a swertia pseudochinensisMethod for determining the content of ketones, said different +.>The ketone compounds include mangiferin, swertiamarin and gentiopicrin. By using the above chromatographic conditions, compound standard curves were drawn, and each compound standard curve was measured as follows: mangiferin (M) linear regression equation is y= 931.37x-1211.5 (R) 2 = 0.9942, linear range: 0.160-1.600 μg), a linear regression equation of Swertioside (ZC) is y=124.52x+4.47 (R) 2 =0.9999, linear range: 0.024-0.240 μg), and belleville gentian (bellevillin, C) with a linear regression equation of y=31.01 x-26.09 (R) 2 = 0.9971, linear range: 0.001-0.012 mug), the standard curves of the compounds have good linear relation.
As shown in fig. 3, the standard substance was separated under the above chromatographic conditions, and the standard substance was separated based on the baseline, as can be seen from fig. 3. And then carrying out methodological verification on the conditions, and examining the precision, repeatability, stability within 24 hours and standard adding recovery rate of the method. The results of methodological verification are shown in Table 2, and the chromatographic methods adopted in the research have good repeatability, precision and stability of mangiferin, swertisin and bellytriazole, and good labeling recovery rate of mangiferin and swertisin, and lower labeling recovery rate of bellytriazole, probably due to lower content of the bellytriazole.
Table 2 chromatographic condition methodological validation
Further, in one example, a swertia pseudochinensisThe content determination method of ketone compounds, the ultrasonic method optimizes component extraction, comprises the following steps:
optimizing extraction time, feed-liquid ratio, extraction concentration, extraction temperature and extraction power, designing an orthogonal experiment, and optimizing the most suitable extraction conditions through extremely poor analysis, variance analysis and comparison of a theoretical optimal combination and an actual optimal combination.
Specifically, ultrasonic extraction method is adopted for extracting mangiferin, swertiamarin and belleville gentione from swertia, and L9 (3 4 ) As shown in table 3:
TABLE 3 Swertian Swiss herbKetone component extraction optimization orthogonal test design
The optimization index is the peak area and the comprehensive score of each compound, and the calculation formula is as follows:
composite score= (a i /A max +B i /B max +C i /C max )*100/3
Wherein A is i 、B i 、C i Measured values of each factor at different levels, A max 、B max 、C max Respectively, the maximum value under each factor.
Based on the above scoring scheme, the results of the orthogonal test are shown in table 4.
TABLE 4 results of orthogonal experiments
As is clear from Table 4, the total score was highest under the conditions of combination 9 (extraction time: 50min, feed-liquid ratio: 30g/mL, extraction methanol concentration: 80%, extraction temperature: 50 ℃ C.) and reached 91.75. The results of the orthogonal test were analyzed extremely poorly as shown in table 5.
TABLE 5 Quadrature test error analysis
As can be seen, the A factor is L 3 The level result is better, the factor B is L 2 The level results are better, and the factor C is L 1 The level result is better, the D factor is L 1 The horizontal result is better, so the theoretical optimal combination is A 3 B 2 C 1 D 1 (i.e., extraction time 50min, feed/liquid ratio 25g/mL, concentration of extracted methanol 60%, extraction temperature 50 ℃). The influence of each factor on the extraction result is as follows: temperature (temperature)>Time>Feed-to-liquid ratio>Extracting concentration. The theoretical optimal extraction condition is compared with the actual optimal extraction condition, so that the extraction effect is better under the actual optimal extraction condition, therefore, the ultrasonic extraction condition of the swertia davidi champ is that the extraction time is50 min, the feed-liquid ratio is 30g/mL, the concentration of the extracted methanol is 80%, and the extraction temperature is50 ℃.
Further, three kinds of swertia pseudochinensis in different growth periodsThe results of the ketone content measurement are shown in FIG. 6.
TABLE 6 three of swertia pseudochinensis in different growth phasesResults of measuring the content of ketone component (n=3)
As shown in Table 6, the content of mangiferin is highest (7.99-20.62 mg/g), the content of swertia (0.08-2.26 mg/g) and the content of belleville gentione is lowest (0.07-0.52 mg/g). The content of mangiferin is gradually reduced in 8 and 9 months, the content of swertisin is in an increasing trend, the fluctuation range is large in 7-8 months, no belleville leaf gentione is detected in 6 and 7 months samples, and the compound is accumulated in 8 and 9 months.
In one example, a swertia pseudochinensisThe method for measuring the content of the ketone compounds comprises the steps of respectively collecting infrared spectrograms of samples of each month, wherein the infrared spectrograms comprise the following steps:
infrared spectra NIR were collected as powder samples and sample extracts, respectively. The preparation process of the sample extracting solution comprises the following steps: 0.1000g (+ -0.0002) of the sample is weighed, 3mL of 80% methanol solution is added, extraction is carried out at 50 ℃ for 50min, the extraction liquid is centrifuged at 4000rpm for 10min, the supernatant is taken out in a 10mL volumetric flask, and then the supernatant is fixed to 10mL by the extraction liquid.
When the near infrared spectrum NIR spectrogram of the powder sample is collected, the powder sample is crushed, sieved by a 100-mesh sieve and placed in a dryer for standby. The collection of the NIR spectra of the powder samples was performed from the envelope, and in order to make the spectra more representative, the spectra were collected at 3 points on each side of the package, and then the average spectra were taken for analysis. The spectrogram acquisition condition is that the scanning times are 32 times, and the resolution is 4cm -1 Spectrum collection range 10000-4000cm -1 Air is used as background during collection.
When the near infrared spectrum NIR spectrogram of the sample extracting solution is acquired, the optical path is adjusted, the spectrogram acquisition condition is that the scanning times are 32 times, and the resolution is 4cm -1 Spectrum collection range 10000-4000cm -1 Air was used as background (n=3) at the time of acquisition.
Specifically, the NIR spectra of the raw medicinal material of swertia davidi (powder sample) and its extract are shown in fig. 4, and the absorption peaks of the raw medicinal material are shown as 7: 8245cm -1 、6838cm -1 、5775cm -1 、5665cm -1 、5186cm -1 、4755cm -1 、4323cm -1 The extract had 9 absorption peaks: 8389cm -1 、6848cm -1 、6350cm -1 、5893cm -1 、5784cm -1 、5163cm -1 、4862cm -1 、4397cm -1 、4277cm -1 . The absorbance is large because the refractive index of the extract is low. The functional groups of the raw medicinal materials of swertia davidi and the extracting solution are similar in absorption, but the absorbance ratio among the functional groups is different, and the difference is mainly concentrated in upsilon (C-H)/upsilon as (C-H) and (N-H)/O-H), which differences may be caused by the solvent system.
Further, the average spectrum, D1, D2 and the corresponding difference spectrum of the raw material samples of each month of the swertia davidiana in different growth periods are shown in figure 5, wherein a represents the average spectrum, D1, D2 and the corresponding difference spectrum of the raw material in different growth periods, and b represents the average spectrum, D1, D2 and the corresponding difference spectrum of the extracting solution in different growth periods. As can be seen from the graph, the NIR average spectrum, D1 spectrum and D2 spectrum of different months are similar, the absorption peaks are not different, but the corresponding difference spectrum shows that the samples of different months are different, the small month average spectrum is taken as a standard spectrum, the large month average spectrum is taken as a sample spectrum, the positive and negative values of the absorption peaks of the difference spectrum of 6-8 months are consistent in all the difference spectrum calculation results, but the positive and negative values of the absorption peaks of 8-9 months are opposite to the difference spectrum of 6-8 months, which shows that the absorbance of 9 months swertia is changed from the absorbance of the first three months.
The NIR average spectrum, D1 spectrum and D2 spectrum of the sample extract of different months are similar, the absorption peaks are not different, but the corresponding spectrum shows that the samples of different months are different, the difference spectrum calculation mode is the same as the difference spectrum of the raw medicinal materials, the difference between 8-9 months is the smallest in all difference spectrum calculation results, the sample extracts of 8-9 months are similar, the extract variation between 6-8 months is larger, and the three compound contents in the sample are combined in different growth periodsThe change in (3)The change range of the ketone compound content in 6-8 months is larger, the 8-9 months change tends to be gentle, and the change of the difference spectrum of the sample extracting solution is presumed to be related to the change of the compound content. The infrared information of the powder responds more clearly to biomass, while the infrared information of the extract responds more clearly to changes in the compound.
Analyzing the bands with larger difference in the difference spectrum, wherein the difference bands of the powder sample are gradually increased along with derivative treatment, and the difference bands are from 5800 cm to 4500cm -1 (NIR) expansion to 7400-7000cm -1 、5500-4500cm -1 (D1) The final range is enlarged to 7400-7000cm -1 、6000-4400cm -1 (D2) The method comprises the steps of carrying out a first treatment on the surface of the The difference wave band of the extracting solution spectrum is reduced along with derivative treatment, and the difference wave band is 7000-4400cm -1 (NIR) to 5400-4400cm -1 (D1) Finally reduce to 5400cm -1 、4500-4200cm -1 (D2)。
Further, three kinds ofThe establishment of the quantitative model of the ketone compound is respectively carried out by the two spectrograms, the sample is randomly divided into a modeling set and a verification set during modeling, and the model is established by partial least squares (Partial Least Square, PLS) and principal component regression (Principal Components Repression, PCR). During modeling, a correlation coefficient method (Correlation Coefficient, CC) is utilized to select variables, and spectrogram processing modes such as multi-component scattering correction (Multiplicative Scatter Correction, MSC), variable normalization (Standard Normal Variate, SNV), a First Derivative spectrogram (D1), a second Derivative spectrogram (Second Derivative, D2), SG convolution smoothing and the like are optimized. The model is optimized by modeling set correlation coefficients (Coefficient of Calibration, R cal ) Validating set correlation coefficients (Coefficient of Validation, R val ) Correction error root mean square (Root Mean Square Errors of Calibration, RMSEC), prediction error root mean square (Root Mean Square Errors of Validation, RMSEP) and residual prediction bias (Residual Predictio)n device, RPD) as an index. And then verifying the model obtained by optimization by using an external verification set, predicting the content of the sample by using the model to obtain a predicted value, and comparing the predicted value with the measured value by taking an HPLC (high performance liquid chromatography) measurement result as the measured value, wherein the predicted value is obtained by the method comprises the following steps of:
y in the formula i As a measurement value, f i N is the number of samples as the predicted value. RPD = prediction set standard deviation/error root mean square; relative deviation (%) = | measured value-predicted value|/measured value 100%. Wherein the data are plotted using GraphPad Prism 7 software (GraphPad Software), the data are expressed in mean±sd, and the quantitative model is established using TQ analysis 9 (Thermo Fisher Scientific) software.
In one example, a swertia pseudochinensisMethod for determining the content of ketone compounds, said method combining said infrared spectral features to create different +.>A quantitative model for ketone compounds, comprising:
according to different situationsThe ketone compounds select different modeling wave bands. Specifically, as shown in FIG. 6, a corresponding modeling wave band is selected, and finally, the wave band is 6135-4300cm when mangiferin is modeled by using a specrum -1 Modeling with D1 with a band of 8900-4300cm -1 Modeling with D2 with a band of 6590-4300cm -1 The method comprises the steps of carrying out a first treatment on the surface of the The wave band of the swertiamarin modeling by using the specrum is 5335-4295cm -1 Modeling with D1 to obtain a band of 7500-4300cm -1 Modeling with D2 with a band of 5588-4380cm -1 The method comprises the steps of carrying out a first treatment on the surface of the The wave band of the modeling of the gentianella marginalis by using the spectrum is 5840-5630cm -1 Modeling with D1 to obtain a band of 10000-4400cm -1 Modeling with D2 with band of 10000-4400cm -1 。
Further, as shown in Table 7, it is known from Table 7 that each model RPD value of mangiferin and swertisin is about 1, each model R value is low, and the model effect is best when the modeling condition of mangiferin is PCR+SNV+D2, at this time RMSEC, RMSEP, R of the model C 、R V 2.19mg/g, 2.09mg/g, 0.5427, 0.5695, respectively; the model effect of swertiamarin is best when modeling condition is PLS+SNV+D2, and model RMSEC, RMSEP, R is the same C 、R V 0.32mg/g, 0.27mg/g, 0.4143, 0.5362, respectively; the model RPD value can reach 3.63 when the modeling condition of the belleville gentian is PLS+SNV+D2, and RMSEC, RMSEP, R of the model can be obtained C 、R V 0.03mg/g, 0.9407, 0.6377, respectively.
TABLE 7 establishment of NIR spectrogram quantitative model of three compound crude drugs
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As shown in Table 8, table 8 shows that the effect of each model of mangiferin is not much different from that of the model of the original medicinal material, and the model has the best modeling condition of PCR+MSC+D1, namely RMSEC, RMSEP, R C 、R V 2.18mg/g, 2.01mg/g, 0.4789, 0.5276, respectively; the modeling effect of the swertiamarin extract is reduced, the modeling effect is best when the modeling condition is PLS+constant+select, and the model is RMSEC, RMSEP, R C 、R V 0.39mg/g, 0.48mg/g, 0.0592, 0.0336, respectively; the modeling effect of the gentian extract of the daisy leaf is improved, and the maximum RPD value of the model can reach 4.17.
Table 8 establishment of quantitative model of NIR spectrogram of three compound sample extracts
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Further, the linear relation between the predicted values and the measured values of the three compound models is compared, as shown in fig. 7, wherein a represents mangiferin, b represents swertisin, and c represents belleville gentione. Of the three compounds, the model effect of the bellyturf gentione is best no matter the sample spectrogram or the extract spectrogram is used for modeling, the model performance of mangiferin is equivalent to that of swertisin when the sample spectrogram is used for modeling, but the model performance of swertisin is greatly reduced when the extract spectrogram is used for modeling, and the model R value is lower than 0.1000, so that the model prediction performance is insufficient. Specifically, the model predictive value and the actual measurement value of the gentianella marginalis have the best linear relation, R 2 0.8844, swertiamarin has the worst model effect, the worst linear relation between the predicted value and the measured value, and R 2 For 0.2382, by combining with structural analysis of compounds, the structure of the belleville gentione is simplest, mangiferin has one glycosyl, the structure of the swertiamarin has two glycosyl, NIR absorption is generated by change of the vibration state in the molecule, the more complex the structure of the compounds, the more complex the interaction between chemical bonds, so that an absorption peak contains more information, which is probably the reason that the belleville gentione model without glycosyl has good effect, and the swertiamarin model with the largest glycosyl has poor effect.
Further, the model is used for judging the model prediction capability by taking unknown samples as external verification sets respectively, the external verification sets of mangiferin and swertisin are composed of a plurality of samples selected in each month, and as the number of samples with the content being measured by the bellytalin is small, all the samples are used for modeling, 3 spectrograms can be acquired by the samples, and therefore, the external verification set of the bellytalin model is formed by optionally selecting one of the 3 spectrograms of each sample. The results of the actual measurement and the predicted value of each model external validation set are shown in table 9.
TABLE 9 quantitative model external validation results
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As shown in Table 9, the relative deviation between the measured value and the predicted value of mangiferin is 1.16% -85.23%, the average relative deviation is 18.25%, but only one sample has larger relative deviation, and the relative deviation of the rest samples is below 37.50%; the relative deviation range of the actual measurement value and the predicted value of the swertiamarin is 2.22-65.38%, and the average relative deviation is 31.31%; the range of the relative deviation between the measured value and the predicted value of the gentian of the daisy is 0.00-42.86%, and the average relative deviation is 19.70%. From the above results, the prediction ability of swertisin to unknown samples was the worst, and the prediction ability of mangiferin and bellflower gentione to unknown samples was the best.
In a second aspect, a method of producing a swertia pseudochinensis is providedA system for determining the content of a ketone compound, the system comprising:
the sample collection unit is used for collecting swertia pseudochinensis at different months as a sample;
a chromatography content determination module for determining the sample using high performance liquid chromatographyThe ketone component is extracted by ultrasonic method to obtain different +.>The content measurement result of the ketone compounds;
the infrared spectrum acquisition module is used for respectively acquiring infrared spectrograms of samples of each month and comparing infrared spectrum characteristics of samples of different months;
the quantitative model building module is used for combining the infrared spectrum characteristics to build different types of imagesA quantitative model of a ketone compound, wherein the quantitative model is optimized using different modeling methods and/or spectrogram preprocessing methods;
the quantitative model optimization module is used for evaluating the quantitative model by using various indexes and verifying the quantitative model by combining the content measurement results to obtain different indexesAn optimal quantitative model of the ketone compound; />
The content measurement module is used for measuring different swertia pseudochinensis in the optimal quantitative modelThe content of ketone compounds.
The foregoing detailed description of the invention is provided for illustration, and it is not to be construed that the detailed description of the invention is limited to only those illustration, but that several simple deductions and substitutions can be made by those skilled in the art without departing from the spirit of the invention, and are to be considered as falling within the scope of the invention.
Claims (10)
1. In swertia davidiKetones (I)A method for determining the content of a compound, comprising:
collecting swertia pseudochinensis at different months as a sample;
determination of the sample using high performance liquid chromatographyThe ketone component is extracted by ultrasonic method to obtain different +.>The content measurement result of the ketone compounds;
respectively collecting infrared spectrograms of samples of each month, and comparing infrared spectrogram characteristics of samples of different months;
establishing differences in combination with the infrared spectral featuresA quantitative model of a ketone compound, wherein the quantitative model is optimized using different modeling methods and/or spectrogram preprocessing methods;
using multiple indexes to evaluate the quantitative model and combining the content measurement results to verify the quantitative model to obtain different indexesAn optimal quantitative model of the ketone compound;
determining the difference in said swertia pseudochinensis using said optimal quantitative modelThe content of ketone compounds.
2. A method according to claim 1, wherein the swertia pseudochinensis isA method for measuring the content of ketone compounds is characterized by comprising the following steps ofThe method for collecting swertia davidi from different months as a sample comprises the following steps:
and respectively collecting swertia pseudochinensis of 6-9 months, wherein 20 samples are collected each month.
3. A method according to claim 1, wherein the swertia pseudochinensis isA method for measuring the content of ketone compounds, characterized in that the difference +.>The ketone compounds include mangiferin, swertiamarin and gentiopicrin.
4. A method according to claim 1, wherein the swertia pseudochinensis isThe method for measuring the content of the ketone compounds is characterized by optimizing component extraction by an ultrasonic method, and comprises the following steps:
optimizing extraction time, feed-liquid ratio, extraction concentration, extraction temperature and extraction power, designing an orthogonal experiment, and optimizing the most suitable extraction conditions through extremely poor analysis, variance analysis and comparison of a theoretical optimal combination and an actual optimal combination.
5. A method according to claim 1, wherein the swertia pseudochinensis isThe method for measuring the content of the ketone compounds is characterized by respectively collecting infrared spectrograms of samples of each month, and comprises the following steps:
infrared spectra NIR were collected as powder samples and sample extracts, respectively.
6. A river swertia pseudochinensis according to claim 1In dental vegetablesThe method for measuring the content of the ketone compounds is characterized in that the combination of the infrared spectrum characteristics establishes different +.>A quantitative model for ketone compounds, comprising:
according to different situationsThe ketone compounds select different modeling wave bands.
7. A method according to claim 1, wherein the swertia pseudochinensis isThe method for measuring the content of the ketone compounds is characterized in that the modeling method comprises partial least square and principal component regression.
8. A method according to claim 1, wherein the swertia pseudochinensis isThe method for measuring the content of the ketone compounds is characterized in that the spectrogram preprocessing method comprises multi-element scattering correction, variable standardization, first derivative, second derivative and SG convolution smoothing.
9. A method according to claim 1, wherein the swertia pseudochinensis isThe method for measuring the content of the ketone compound is characterized in that the indexes comprise modeling set correlation coefficients, verification set correlation coefficients, correction error root mean square, prediction error root mean square and residual error prediction deviation.
10. In swertia davidiA system for measuring the content of a ketone compound, the system comprising:
the sample collection unit is used for collecting swertia pseudochinensis at different months as a sample;
a chromatography content determination module for determining the sample using high performance liquid chromatographyThe ketone component is extracted by ultrasonic method to obtain different +.>The content measurement result of the ketone compounds;
the infrared spectrum acquisition module is used for respectively acquiring infrared spectrograms of samples of each month and comparing infrared spectrum characteristics of samples of different months;
the quantitative model building module is used for combining the infrared spectrum characteristics to build different types of imagesA quantitative model of a ketone compound, wherein the quantitative model is optimized using different modeling methods and/or spectrogram preprocessing methods;
the quantitative model optimization module is used for evaluating the quantitative model by using various indexes and verifying the quantitative model by combining the content measurement results to obtain different indexesAn optimal quantitative model of the ketone compound;
the content measurement module is used for measuring different swertia pseudochinensis in the optimal quantitative modelThe content of ketone compounds.
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